Benchmarking protein-ligand co-folding across Nav, Cav and Kv-family channels

All-atom protein-ligand co-folding offers a route to modelling biomolecular complexes without prespecifying the receptor conformation or binding site, but its reliability for large, state-dependent membrane proteins remains uncertain. Here, we established a training-cut-off-aware benchmark of experimentally resolved ligand-bound complexes of voltage-gated sodium (Nav), calcium (Cav) and potassium (Kv) channels to evaluate AlphaFold 3, Boltz-2 and Protenix-v2 across multiple ligand representations. The final production set comprised 301 completed method-input jobs and 7,525 predicted structures generated from RCSB/CACTVS SMILES, Protein Data Bank Chemical Component Dictionary identifiers and matched PubChem and ChEMBL representations. Executable coverage differed markedly among methods, particularly for Kv-family systems, necessitating restriction of the balanced pose-accuracy comparison to 22 Nav and Cav complexes completed by all three methods. Median top-ranked ligand heavy-atom root-mean-square deviations were 19.85 Å for AlphaFold 3, 22.12 Å for Boltz-2 and 20.25 Å for Protenix-v2. Best-of-25 selection improved pose accuracy, but recovered a ligand pose within 5 Å of the experimental reference in only two, three and three systems, respectively, indicating that insufficient sampling was the predominant limitation, with ranking errors contributing to a smaller subset. Same-pocket recovery remained below 50% for all methods, despite broad preservation of receptor architecture, and method-native confidence measures showed limited discrimination of ligand-pose accuracy. Alternative ligand representations produced small aggregate changes but substantial system-specific effects on execution, pose category and ranking. Approximate close-contact screening identified additional geometric concerns in a subset of predictions. Collectively, these results show that current co-folding methods remain unreliable as stand-alone predictors of ion-channel ligand-binding modes and highlight pose sampling, pocket selection, ligand representation and independent structural validation as priorities for methodological development.